Robert Grissom

• Doctor of Philosophy
• San Francisco State University

• more software references for calculating effect sizes and their confidence intervals including SPSS, SAS, R, and S-Plus

Most broadly defined, an effect size measures the strength of association between variables or the degree of difference between parameters. If a null hypothesis is false, an effect size measures degree of falseness of that null hypothesis. In the planning of research, the anticipated effect size, or the effect size of minimum interest that the rese...

Cross-cultural research is now an undeniable part of mainstream psychology and has had a major impact on conceptual models of human behavior. Although it is true that the basic principles of social psychological methodology and data analysis are applicable to cross-cultural research, there are a number of issues that are distinct to it, including m...

The goal of this book is to inform a broad readership about a variety of measures and estimators of effect sizes for research, their proper applications and interpretations, and their limitations. Its focus is on analyzing post-research results. The book provides an evenhanded account of controversial issues in the field, such as the role of signif...

Statistically significant differences in culture means may or may not reflect practically important differences between people of different cultures. To determine whether differences between culture means represent meaningful differences between individuals, further data analyses involving measures of cultural effect sizes are necessary. In this ar...

Estimation of the effect size parameter, D, the standardized difference between population means, is sensitive to heterogeneity of variance (heteroscedasticity), which seems to abound in psychological data. Pooling s2s assumes homoscedasticity, as do methods for constructing a confidence interval for D, estimating D from t or analysis of variance r...

Traditional parametric (t, F) and nonparametric (Mann-Whitney-Wilcoxon U, Kruskal-Wallis H) statistics are sensitive to heterogeneity of variance (heteroscedasticity). Moreover, there are theoretical reasons to expect, and empirical results to document, the existence of heteroscedasticity in clinical data. Transformations to reduce heteroscedastici...

The "probability of superiority estimate" (PS) estimates the probability that a randomly sampled client from a population given a treatment will have an outcome that is superior to that of a randomly sampled client from a population given another treatment. The meta-analytic clinical outcome literature was examined to calculate mean PS (PS) for com...

Comments on J. S. Hyde and E. A. Plant's (see record 1995-21144-001) comment on A. H. Eagly's (see record 1995-21141-001) discussion comparing the sexes in scientific research. The author points out that if Hyde and Plant's purpose is to determine if gender effect sizes tend to be smaller than other effects then chi-square is insensitive to the o...

Comments on J. S. Hyde and E. A. Plant's (see record 1995-21144-001 ) comment on A. H. Eagly's (see record 1995-21141-001 ) discussion comparing the sexes in scientific research. The author points out that if Hyde and Plant's purpose is to determine if gender effect sizes tend to be smaller than other effects then chi-square is insensitive to the o...

Parametric and nonparametric approaches are compared for testing hypotheses of the superiority of one therapy over another when the outcome is ordinal categorical. The estimation of clinically informative effect sizes, especially the probability that a client given one therapy will have an outcome that is superior to that of a client given another...

Appropriate statistical analysis of clinical data based on ordinal categorical outcome scales is discussed. Chi-square analysis is inappropriate for testing the superiority of one therapy over another when outcome is ordinal categorical. Emphasized is estimation of clinically informative effect sizes after statistical significance has been attained...

An intuitively appealing indicator of magnitude of effect in applied research is an estimate of the probability of the superior outcome of one treatment over another. Parametric and nonparametric estimates are discussed, as is a meta-analytic estimate. Estimates from values of t, the point-biserial correlation, and standardized effect size are pres...

Memory retention of a short verbal passage did not change significantly in subjects who were isolated in a dark and soundproof room for 24 hours between the immediate recall test and the terminal recall test. A significant decrease in performance was noted in the control subjects who went about their everyday activities during the 24-hour period af...